{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "User's Guide, Chapter 25: Post-Tonal Tools (1)\n",
    "=============================================="
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The music21 toolkit features many tools for analyzing and creating music within\n",
    "a post-tonal context. A :class:`~music21.chord.Chord` can be identified as a\n",
    "Forte class, a list of pitch classes can be used to create a 12-tone matrix,\n",
    "and many other analytical tools are available. \n",
    "\n",
    "This overview will illustrate key features of music21's post tonal tools. For\n",
    "complete documentation on post-tonal tools, see the many methods in\n",
    ":class:`~music21.chord.Chord` as well as the objects in :ref:`moduleSerial`,\n",
    "such as :class:`~music21.serial.TwelveToneMatrix` and\n",
    ":class:`~music21.serial.TwelveToneRow`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pitches as Pitch Classes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Any music21 :class:`~music21.pitch.Pitch`, or a  :class:`~music21.note.Note`\n",
    "containing Pitch, can be expressed as pitch class integers using the\n",
    ":meth:`pitchClass <music21.pitch.Pitch.pitchClass>` and\n",
    ":meth:`pitchClassString <music21.pitch.Pitch.pitchClassString>` properties. \n",
    "\n",
    "In the following example, the :func:`~music21.corpus.parse` function is\n",
    "used to create a :class:`~music21.stream.Score` object. The\n",
    ":meth:`id <music21.base.Music21Object.id>` attribute of each contained\n",
    ":class:`~music21.stream.Part` is presented in a list. \n",
    "\n",
    "We'll start our look at post-tonal music with a most-decidedly tonal piece, Beethoven's Opus 59."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Violin I.', 'Violin II.', 'Viola.', 'Violoncello.']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from music21 import *\n",
    "aScore = corpus.parse('beethoven/opus59no2', 3)\n",
    "[e.id for e in aScore.parts]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can view the fourth and fifth measures of the violin Part by obtaining the\n",
    "Part from the Stream with :meth:`~music21.stream.Stream.getElementById` method.\n",
    "Next, we can extract the desired measures with the\n",
    ":meth:`~music21.stream.Stream.measures` method. Calling the\n",
    ":meth:`~music21.base.Music21Object.show` method will, assuming correct setup of your\n",
    "environment, open a display of the extracted measures."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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qHHYhEeR5ZOHxA4m8w3U+S0+b/PfMGusXe0cfQPs7V1fVSIF7E6PShm2YAfZu\nIyEeRKTcyCynt1EwqTQQvaasaCKb9LH4mV0f5/iYrlYQ160nEb2hj6Neg+TDiXlpHka9UQNPYOoI\nnTPrVrLgG9Sb0HhjyudC6Pdc+x3KR4scQXSaaOrWHutxKJ3pP1fQLKd9JnWuqTsXgiRJUt+qJgZt\nMfrh9Knh0tlSlYd1aWKbXi4UIYZZl5W3guk/aui/Ka/7j2puP58Y2p16H35PDMst3sBMEEGQt9NO\nd1CcZDNbqnIDT1dZ3ZukiMlsCPyF9DFtkQ6INU0RM5foEVss/7091LsolcLhZQMoe9DuSfSIbBEN\nF9M1vdOo7Eg6HUQ2RL1uvupUerGDeqzbo0vK+muPZUF6zoDpmiIm82XS788pXbbN/2ZdRPfON6dX\n7KtbYHQe0ZhS3O7dXbarIzWhcp0J/VLzytTJBb5nbv1juqy7gKkTDg56qRr9BYNLEZO67mqaIubr\nJWV06xTxlsS+B7WsoXrk42MT2zVJEQPl6TY+XXNbU8QM3r2BX1L/c3Ih7Yb4KicXtkuNdB2kVLqz\nfgPHSxPltqgezTao804mGzU7rGU103+eIEnTkD3YJfXi6i7Pl80GP0xV+7uF6NE4Kn8iLszmFx5f\nSPSW6iXIOiofJXqgFyeF3abm9quJgNfnKZ+w7r5EcOZqopffOqIX8060h9dfTfSm34vyPMCn16zL\n+uIO4mb+j6QDFy+dfP4rfe7rnpQPe17ZZ7kQQc8DSx6vyvU8DnOIXlDZ9dHzieDybHYpcbP+GcoD\niIuJeTfq5E0etAeWPHbFyGsxfu8hPdLlYcC9SI9CygegP8jgRsOU2ZvyXsMrBlD22ZSPFDuA7oHy\nnxJpoHYrPP5UorG9avTKcZP/3kz3BuB9mDoa5HPEZOODMore64PUKnmsWxrCYoPcecQEkIO0mMH8\n9mnm+BPxm/IkInVU8Vq4aGfi3LEf6TQzc4hc6HmD/L6nlP02Qv/n2kuI+6qy8/j+9Jb6phf3L/z/\nXPrLL19mI0Z7/yhpPWCAXVIvLujyfPEmddiq9lc2/HiYVhMXemV5y5cwvQPsK4jg+H8XHt+6ZN2U\nlUSg51Sih0nZtttOLnnXET2xP0YEKt6YKP/HDeqyvriEmHDpZ6SHj3+ayCXZT+/dVE+sVHqQJlJp\nEwadQ75fr6XdEPB+4BNjrMt0spbISX0fynM834fxBNjLUkndMvJajN9fiXNuauelbAUAACAASURB\nVNLZ/yGCxUXbA0dP/n0z6fkSBiV1jukWUK0jdY6p00C8jmhgLo4G2gw4CvhSYrsFRE51iNRmd3TZ\nz71KHvsaNuI1VTyOVxLnbo3W1vTXoWYV9eb7GKUW0VnhVODDtM+PKXedXO/YxPO7MPUYdTtPDMJO\nicf7vZ5rEefasg4TdTvjDELxHutyPAdImgame7oCSdNT1eRQEBeco1S1v265w4fh34nHU/k+p5PP\nlDzWNAi6jgj43oWYhOhHlPcAvJoI6D+ZGHb6TuKztZTyYaynMf1uxkblNKrTqWxATOzYrcdVldS2\nxdyhvfhX4vHpFGA/GnjT5N/foHqS2dloFVMb3zI7j7IiOXcpeazXyTJnuqpUTk8i5mwoej7tRrtP\n0ns+3LrGcY6p20B8EuW/U1WTnR5B+xzWbXJTKA9GNmnAVty7FicC9RiOxyuAf/ax1E0/OA7XEh0b\nnk35KIu8Y0inkiv7bA6i00I3qRGPg5gjq99zbb/mMvUcMMrgviQlGWCX1KuqSdPuNrJaxI15VQ7E\nU0dVkZzUhH0zoWflP5k6hLTXIZK3ED2AjyDep82Jz8aexMXwnYheP1+ls0dPKtVB3dyk66sPAV+o\neH4pcSx7nSQtdUPWLa9yHanvxKgnRE65N9HYAzFh4lOIXtvq9BPKJ4wcdVowiFGYm5Y8XpU7eX32\nU9INyvOYmot8QyJ4BJEW5sQh1StvmOeY1Oiwug3by4hc9kUHA3sktskmN/0d1Z0OMsWgEBgYamoT\nps7j4jHUsHySSHm4ust6qd7TZee8UfxepjovTIdzbb82Zeo5oDgqVpLGwgC7pF5VBdh3Z3Q9GYp5\n+IrGEWBP9QIcdbqaXpRNwHTtgMq9iciVes5kmWW9gjagfFK6ZUQP7dmsRYwI+GPFOocRqXl6kcq9\nPIgbl9R34sYBlN2vOwHfIz57pxK91rrdTM9mo8qx2k0qSDETRgoNQ4vqXuzPpnOOhf+iHfD9BnDZ\nkOqVlzrHVE2OV1eqAbvJOeYjicefWfLYdsTcBFCv9zqUz3FRZ5JEtZUdwy0YzCgIqcw3ifmFquan\nOJjykVxlAfatmBogHrRUB4Hpcq7tR1lD5ZbUn2xdkobGALukXp1BdQ/PQ0dUj8MqnrucCOiOWtkk\nQmuZGT3YIXJ+5103wn0fS3njzHuonmhutlgOPI7qRo9XEkHipq5PPD6IlE+ptB2j/GyVWQx8lwiy\n/4aYUHYQEy6uz8oaV68ZeS3SN9Pj6E0/XXyN+N0rs5h2j/U5wEtyzxVzjw9L6vs+iHNMapLBJueY\nvwJnljx+DFPzxP8XMVroFqKBoo6yc8t0m+h5uis7hhOUT3Cr2Wlr4HAGm4LuFOD1XdYpu+8pmyh3\nc8pTdg3SdD/X9qPsmE4A9x3R/iUpyQC7pF7dSnX+xNRka4NWFWD/Nt1zJw5DWX7F8xhPXXpR7G18\n5Yj2Ox94ecnjVwInjKgOM8FlRL7wqt5UnyVS8TSRCrDfmf6HFS9IPD6I0RG9WkT0xt6PGBVwBLM3\nf3cTxQY4gKtGXosY1VJmD4bfO3C6Wg18sOL5FxMpdA6jncrtDOBPQ65XJvV935H+eyAP6hxT1ot9\nCdGwmZmgnR7mS9Q/b5SlVtiXwaRtmC1S6SkOHmktBPAaIs1br8u9h1SvHYEfA68bcLnvY+oIz7yy\nVFKpkavDbhBKnfcGEWAf9/Vc6hxw0Ij2L0lJBtgl9eMtFc89mvRF2KDsDuyVeG4V8O4h7z+lrNfM\nr0Zei94V8xqfNqL9vpLyIbZvoDNHu+CXlKfSyWzU5fkyqcl5If09qysVQPp9n+X2aj7R2/fBwN+J\n3m6pPPHqVBZMvGLktYiew2WjqLYgGoVmq0+RHi21HTHHxTh6r0N6cjyAvfssO5Ua6LcNyzmZ8kBR\nfrLTA2gHquqmh4HywNBcuqe6U9sKynuwHjLieijeh9v6WIbVoH3B5L9PZ7AjmlYBn6t4vmwS51TH\nhUf1X51KqXPt3vTfAJ06147qeu52yn/7Hzii/UtSkgF2Sf04i+glUmYr4JFD3n9ZXtTMp0gPlR+2\nskleZ1KAfWnh/6eMYJ/3oLy30V+Ak0aw/5noY0RP9UG5gHTvrIf2WXZZ3lyonsthWOYQx+0xxE3o\nYcyM+RGmi2KqDBjPXBct0qNrZnNv1mxy6ZQ3Ew1KEI1qPxh6jdrGcY5p+tlcSVw/FD2QdlA9673+\ne+DsBmWnGjGPaVBGN88letWvz8qO4wMpb6DvxRIiZZhpZ2amZcRv+obACwZc9ukVz5XN3XIesK7k\n8ceTnvS5qf2YGtNJXVttT/k9ShNl59r/Y3Sp4lqUnwMOZXBzWmxBpAvbb0DlSZolDLBL6tebK557\n+hD3u5DI111mFfDOIe67yjzg7oXHVgE/G0NderE5sGvu/xcA5w95n/OIgGdxxMPNdE+FMt0tSPw9\nCC3g+Qyu11CLdDDq8MTjdZUFPq4mJrwdpQngw8BTiFQnD5msRz+WEOllZoti7tg/AhePoR6Q7p3c\nyxwE083C3N9Nzx0nkJ6od/vc3x+gPPgzLMM8x+xS8tjlwLk9lPUJyo/LM4nRQU+Y/H+T3usAv0s8\nfjQxD0S/9iLe03HMiTBKZd/7CeL3sF8TwKeJnr5VIy40vWXXrS9nMBN7ZspSpGXKriVuBf5c8vhC\n4L8HUJ/DiGvAfQuPn0V6cvlhXM+N+h6n7BwwB3jeAMqeIEYq3JPqkZ2SNIUBdkn9+h3wmcRzhxMX\nKMNwLOneH29hfL3X78PUYMjXGG+u6SaKF94nDnl/E5P7KJuc6DjaQ31nqs1zf29Aee/ffqwAjqL/\nIHHmy4nH70N/vQOLN38Qge5Rz0vwDqKH51VEepjL+ixvgujt+qQ+y5lJij266k7wOAy/Tjz+cAY7\nwd04bJ74u44rgK90WedG4PMNy4X+0wsM6xyzT8ljvZ5jLiMmPy46FvhPIuXVrcDXG5Z7A+UBm3nA\n8Q3LKlo8WZ/5DP93e9xSDRXPoP/0UM8DjiQCbKl5Hqarhd1XmTWy79li4G0j2mfqc3lG4vFXUH7e\nqmsn4KvESOI/Fp5bQ9x7lOmnAXqCqem81hEjKkcpdayfRf8NKi8iUvh8BlMHSpKkMVgE/IG4kS0u\nv2HwjXnbEjc+Zfv7bsP9LU2U0+vN7ntLyhrWRE7D8DPa9b6S8glbB+nVlB//cY1AGLS70fm6BtmT\nKu9AYqRE2bFscjwniKBlWRnv66N+fyuUdRNTc/0P26sm930dU0eZ9OoZk2U+YEDlzQS/pP0+XkKz\nySmfQvlnq9fJyZYSuVjLyvxwD+U9JFHW0T3Wrx8fze3/5B6235Py15Itb+2xXn+sKHPjGttPEEPv\ny7Z/T491AvhHoawbSecKruPQRB1vmfz3oz2W+5ZEuS06J1JtYhHtSd0/3mXd7JxVXO7XcJ9vTZTT\nNO3F10rKuK3LNlsQjctl+/810cjQi4dOlnsbU0fq5D02se+mPYPXlJTx6ZrbnlKy7Upm7wTPRW+g\n89j0m4Iq8wDK3/ubSTdw3D2xTQv4J7B1D/XYjDgXryRSLJbZhfLPWIvyTi113LOkrC/W2G5Q553M\n1qSvec+g93PAwyfLvZXBjCqSJEnqyQ5EL+2yi51nDHhfZTdkLSLXYdOg3dJEWb0E2DcggtL5cv63\nh3LG5WA66/7cIe/v6ZQf+1ez/twkHkDna0vdCA3Csyg/ni2aNVgclijjZnoLWJXdXL6mh3L68fzJ\n/S6j/8kUM4cQwZh/sP58XrvZm8738TENtx90gB3gW4ky19C8d+B/JMo6to/69Sr/O3daj2X8iPLX\ns5LeG/suSZTZon7+28MT2y8jPSFylbLGhH57hE8wNWifX3o9j+xAulHoFpoHAjclPh8tovGw26SO\nww6wNw0W9hJgB/hCYv8toldv084B/0mkVWoRaUWqHJnYb5MA+5xEGXUD7N9JbF+nkWs2+E86j8s1\nROecfr2B8uNeNm9D3k8S27WIeRyajLjanpicvc5n9aTEPruNcEopfu9XUC+n+6AD7BCvIXVMv0Tz\nEaNPpd0g8T991EuSJGkgDiZa/YsXOjcTPWwH4aUl5beI4P4ePZS3NFHeu3oo6xUldRp2moI9gQ8R\nPRw/ANy/x3I2JIbUZnX/OsMLGs6h/OZ8FfDkIe1zXIo93Q4b8v4+TvnnuemIgHzv2fzyoR7q9MlC\nGacTKRFG5b8m97uSmHh5yx6XrYgA4gOJ71rWe+olo3spPdueGEmzYR9lzCF6hmXv4+dpfo7I3ovi\nckgf9So2YuWXy6mfMmI+6Z7Vo0oxkHdabv+95BGHdC/sz/VY3gRwR6LMFpHmpa5PJMp4fw/1+myh\njF8Ac3sop+gFiTr+oc9yv5wot0UE319D9x6YE0Rv2r/mtq2T+uGZif02DXS9I1FO0wkUv15SRp0A\n+z6kGypaRN7ruya3btsCeHtuu9/R/dgfndhnkwD7FokyUikXi1K/9VU9kwedom4625/y720/o1oW\nEemjiuXeQvcGywOo/rxeS6Saq/pNnUs07mR1+BXdz3NLiDlSyvbZ9H5hI6Z2pHpOzW1T551+Gtf3\nI9LTpI7pWcDuNcrZkrjna3IOkCRJGom9KL8AvYMIbvVqDuXpV1rE7PU79Vju0kSZ10w+V9dORNqL\nfBmP7bFOdW1Ne7h6fvk+9W4sM/PovMn9K83SPjSxEeU9Ti+lvyDbdPVuOl/nm4a8vwWUp3hpGmBf\nBPyppJx1NGss25fOm8prGF6anDJHkh4iPYhlBd17jI7bB2nXdznR4LF95Rbl8qktvkxvjSTPo/w4\nPrGHsvLyr7G4/APYrcv2GxOjjVJlXEbn5M/DtoBomM7XoZc0AhOUf4/v1WO9lpSUlV+ajGhYRARB\ni2WspVn6gv2Yeo4ZRE9ViGBcWaeBfkflbUV6xF+2XAC8krimylJPzCF6wD+RmOQvv37dTgEvS+zv\ngIav4SOJch7UsJwflJSxgnqNd6kgf7asIXqyPor4/mRlbkQEYD9ABPOz9a+iXoNcarTYw2tsm9k9\nUUbdnsUvSWz/wcT6zyWus3oZITITpc5Vv6L33+z3J8qsO7Hm2xLb55eziQa2hxIdaPYnvu+vJUbp\nZutdSP1rqf2IDgZlv41N8vYXv29NOuK8uGT/LXpPi5V5T6LcbFlNjHZ5FHHezeq7mGhUPAG4Pbf+\nFYz2GlWSJKmrO1Gep3UNkaqhaU72JZT3cmoRweR+hsQuTZSb3ajvX6OMLZmaY/pZfdSprsdQfVH5\nPrqnzFlEDKfOtjulxja9ehRxU5Cv53Ii6NxPz9rpajFTUwZdyvBf67bETUJ+v73ktM8PQ84vV1Fv\ntMjWdI6KuJLhTXpc5jDKbyoHuXxhZK+mN6kgzgqiwbLOCJsJ4PW5bT9H7yMQTkzU54Qey8tsQAQm\nUu/THURw4C50BgQWEamqrp5c74cVZWRBjb9RPgHmID21ZN+v7bGsJxbK+Wkf9TqmpF75pVv+76Lt\ngXNKyrmCeo3E2xCB6Px2gz7HFEfz3MpggpSPobpHa35ZRwSBUo2Fn6d+j/1PJ8po2gHip4lyml77\n/DNRzk41tl1IeQNSallBXHOUPXct5ZNxl/lAoozjam4P6TQzdUdHFNN1ZcsaIj1Kdp7bmHYQ8o0N\n6rc+uJHyY3QpMeK2rgni/FtW1rsblLOAzlFgvS7X0L3RuOhIyuct+NZkvbp5FJ29xb9LszRMqRFL\n721QRpkN6BzF08854BqiQVOSJGna2YjoSVM2Cc2fiVQg3QKNS4kbgrKL5GVESpZ+h4EvLSm7RTsw\nt4rIrVjWe3ECeDCdQeN1DD93eeb+dL+YvIa46Ss2aswhbqiz4MYqonfNMFJ33IVoCCnW7Zs0GyUw\nk+xMZ4qH/HIKg+thmbI/ncHlXieN3ZzyG8JrqO7xuA+dva3OY7Tv9YF09koa1tJrSqZR2Yfq+t9O\nNMSlemztTXvi42vpb7LPXYEbEvW4hThP9GNL6gXbricajs6n8/fpBNLzD+SP15eJ8/4wzCHSBJT1\nml5NDLNv+ps3D7goV07TiRgzB9JuiEgta4g8+00a0ZcQvUqLZV1FdQP3vnQ24J1L7yPZqtyjUK+P\nDbDsJ9L/CJv3UP94LyE+/2XlNGks3Il04+UfqZ9eIRUkblF/Et4lRCqIfo7hhdRLJQERsC4bpdki\nfivrfD/nAj9PlLGOeo1EE1QHFq8leihnQdWf1Kzb+uQPVL/vXyF6Mad6YU8Qo2lOTWz/noptUzai\n/Zvay7KM5nOLZA6i/H7qR6R79c8h7mnyv5Wfotm9wu5Evctez03EZKz92ILqybfrLOfTvNFCkiRp\n5HYFvkH5Bc1y4JdEr7c3A68jhjl/hbhZLtvmNuLGa7MB1W9pYj9vonPyrbXERfZ7iN6cJxKpafLb\nnMtoA25zKA9cly2XELk9TyBSIVyVe+47DP7Cci5wBHHhnu/1soYYjTConPzTxV2IiRDfRuQY79Yz\ncSXRA+h4Im/uoD7Pecfl9tdrgB2il+DxlAf9vku87oOJ3ORPB75N+/WvIr4zwxoVUWZvpqZrGsZy\nDtN/ctM5wF/o/lpWT673WeLc9zHaPcKXE73Pms4nMUFMcPs84pzTbTTBzURvtqOI4Gkvw/g3JT3a\nqeq1v444Zz2k5Pk1RM/2JzOc9AoPJ4bPf4rqCUSz5WKiV/WziRzcdbyI5p/ZRxDH5cuU9zKvWi4i\n3oc3Uq9n9CIiLUI+XUeL+O34Du1zzCHEOeY7tH9XVhHXDf3kVu4mawBYR/1AbF0Po977Xlwuo3tj\nyQQR0LsrcQxTvcWz5evAo4mA16JCOUuIHPsvJ+Y2qCrnt8ATiIbmYjlLifR57yYddMuO9TuIuSPu\nTHUv202pzmtftXyU7qMg5xPXsscydbRi2Ws/hshFn+/hO4cY3Xkk3Xsx30D0mN6P6nR9D6I6B3W2\nfIHZlX89k58E87dEbu2ya7Mrid+o9xDnvLcRx+z8knWz9+dRfdRrETGfTd0RLNlyGv0Ho5cSnVuK\nZS8jUuA8hrg+Pxx4FZ2jGC8lvtfdfkMmiIbJ5xPzQ5V1tMovNxHng8cRv/2b9/C6+jkHnMjsSZ0k\nSZLWE/clerTnh3PXXVYSwe2XE0PCB2lpYp/HEzdEL6L6JrBFBB9ewXhuYOYSuZHLhn52u4H7AM1y\ntXezPTE0+RNMDRj8gcgnW3fCwZnmlUQgrtdlvyHVK0vJ0U+APbMN0du5TjDoWiLX96CDUXX8nP7e\ni7rLC0f1gvq0LeV5jrst/ybOa1v0sd9+ju8VPe4XIhB7GtUBjLXEaJL8dy8fYP8N0Tgw7ImqL6H3\nY/SbmvtYDFxHBKfrOruPeuWXcxrsczvid+lSun8+ryF+a0bR6zCbnPfbQyp/Q6Ixos7r/hfxuawz\nT8pien/ffj6gci4YUDl1UnEcTFwrrqH7NeXnqD8Xwct6rPO3cmXsPYAyyjyV9MTDFxKjXqZ7Q/Cw\nvIk4DifRPgabEQ08HybdkSe1XEc0BA6qQ8Q+wPfo3vh8BvHbNMj38QHEZ6vOSL+/ENe4ddMbbk9/\nvxmX9PG6Hkj7GrDbOeCzjDZtoaRZYLb+4EoanwmiZ88jiZ5JuxABjA0nn1tODGG8kuhtdRrRI/j2\nIdVnKdHbruhVtIOSGxO9DO9NBADWEj24Lid6xGQ92cdpMVHHRxBB7K2J4zqX6BV4LXGz9X/Exedf\nidcxKEfSvhFsETcuvwHOnNzfpQPcl+qbTwShfk3cTAzCBJGn8gAiiLrt5H6umlzOJt73QX6+1L8d\niO/pIcT5YWvi3LaMOOfeSJwjsu9tPwHu6WIr4ry4lDh3LyLO25cQo2uuLKy/O5EG5yuU/y5oNCaI\ngOQBRMNedo65kvY55reM7hyzkEix8eLJfQ9L9roPIj6v2xG/4TcQgfUzmR7XG9Pd5sQkkbsSx3AJ\ncQ15GXHtcwaRlmp9sR3Rs3hP4hx3DTHq4gdEoHG2OpIYBfFkIjVlmW2JYPPBxO/E1sQ5Zy4RUL+O\nSEH0C+L7t2II9dyE6DG+GzHKYTOiV/ffiQaj84ewz8wGwKHEb192PXcbcZ69grj/mom/hUvoPAds\nTpwDLqV9Drh1bLWTJElaTy0l3YNd9d2ZuMHbi2YTH0mSJEmSJM1Yw5jMTpI0+1xB5G+VJEmSJEma\nNerOOi9JkiRJkiRJknIMsEuSJEmSJEmS1AMD7JIkSZIkSZIk9cAAuyRJkiRJkiRJPTDALkmSJEmS\nJElSDwywS5rtJhKPLxppLSRJkiRJkjTjGGCXNNulAunbjbQWkiRJkiRJmnEMsEua7XZMPH7nkdZC\nkiRJkiRJkqQZ5sNAq2S5Cdh0jPWSJEmSJEmSJGla2gZ4NbCW8gB7C/glcBCwYEx1lCRJkiRJkiRp\n2vgUcA3poHpquR44B3jI6KssSZIkSZKk6WjeuCsgSSP2S+C8Pra/fFAVkSRJkiRJkiRJkiRJkiRJ\nkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJ\nkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJ\nkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJ\nkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJ\nkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJkiRJKpo77gpIkiRJkiRJkqaF\nCeC+wJ2AK8dclxlhYtwVkCRJkiRJklTpQOBdwC0V6ywGTgT+dyQ1Wr8dCHwAuL7LeuuA2yaXi4Hf\nA2cAq4dZuSGYAzwYeDrwCGBj4DTg0HFWaqaYN+4KSJIkSZIkSap0E3AH8CBgg8Q6fwN2GFmN1m83\nAVcB9wO2abjtOuAHwHHAjQOu1zDMAc4C9i08fvsY6iJJkiRJkiRJQzMX+DnQyi23AzuPs1LruRfR\nebyXAwcRjRk7AA8Fvl5YpwXczMx5XxYADyMaFrL6f3+sNZIkSZIkSZKkIXgsnYFcA6HDtTUxeiA7\n3pcBixLr/YPO9+Z8YP5oqlnbS4H/KXl8DvBX/Fw1NmfcFZAkSZIkSZJU20zL770+WJv7OxUwvxY4\njOjhnlkK7D+kOvXi3sD7Kc+t7lydPTLALkmSJEmSJEn9uxL4de7/c4H7jqkuRZsAp0z+vbZqRTVj\ngF2SJEmSJEmS+tci0qzkrRlHRQrmA78Atpz8v6MgBsgAuyRJkiRJkqSmjgW+AnymsHwBuEtuvcXA\nl0rW2T63zl2Ak4g0Ky1gJXAN0eN6j8T+5wCPAn5K5DpfRASSPzS57XLgtsn/jyoP+hzggYXHrq5Y\n97+BfxN1XU5MWHsKcI8u+7kH8EPi9WXbXgK8hqnx3m2As4n0MJl7Ax8GPpvYBuJ9ADgaOIuYAHU5\ncAPlOdyLtgQ+AlwxWdZaYuLXM4EnFtbdnKmfkexz8orCusfS+bn7ApFXvqjJMYLp+XmSJEmSJEmS\nNGBHMD0mOT0SWFaoSws4Fzg4t95GRCB3ZW6d84gA7ATw8dzjlwBvJF5T9thq4EG58u4C/JboGZ6t\ncwGwLxEELtanBfyB3oOiWwO35sq6evI1lXlQYb/LJ7cv2pGYLDULPF9VUufjE/t4a26dm4igfH67\ni2n3VAf4VEnZ+eXGydczl85JTr8HfK1iu68m6gfw4tx6twNfB35W2P7vuXpuCJxcso81wMfofO8e\nS3zGsnXWAi/v4xiN+vMkSZIkSZIkaYymS4AdYCFwOZ0B0V0T676bdvAyC04+k86gZb5n8WsLz2Xu\nAZwK3EJ58PMnwHuBOwqPP7nH11gMsF/G1ODqQqJXdz5I2wJeXVLezrnyTiZ6SkME3c+j81geVNg2\nC5avIHpbQzRSvLKw33we+PnAAuBvued/QxzrRbn9FwPs2XIbcALwicLjq4F7lby+D+fW+T2djRH3\nofN9uX3yeGSeU9jHT0vKZ7LM7BgW39emx2jUnydJkiRJkiRJYzSdAuwAT6CzPmVB5TlEUDcfmJwD\n/DK33bcL22xNO6i5Atit8PyjC/u9Fdg/9/zOdAZFez1OxQD7GqIH9TlE0Pp8pgbW/0WkVimaSwSd\nW8BfSp7fs1DWGbnnHky7x/bDS7b9caGO+eB8MXhedizKAuw/oB2AB3hc4fkXFMp4cO65a4mJVYsO\nKpRxNu2GlfnEsetWRjZSIN9Yk99/L8doVJ8nSZIkSZIkSWM03QLsC4jULll9LqIzKAuwOxHQvJZ2\nj+ZiQPfUwjb5wHZZb+n8cVhD9I7Om6Az1cygAux1lp8Ae5eUdXBunWJwGiJYfEFunduBO9HZGHE1\nU48vwJMKdTgh91wvAfZLmJqrfCGd7/UXC3XPb//Okn1kvl6o61G5544pPPe0ku2/OflcPhd8v8eo\n58+Tk5xKkiRJkiRJ6tUqIi1IZkfgAYV1nkEEcL9KBI0hehm/lAjYng+8qbDNNpPbkFs/pUX0Li4+\n9q8ude/FdcBOxOvci+jVfQLxOjIPJXqo/4DOHtZPyf19ApHDPr9cD+ySW2fh5P+3A/abfGwbYtLN\n4rZfKdTz3vTnT8C6wmNrJveV2Sz39860J6RdS7z2lI8X/v/03N/fLOzjOYV1twIOJ97vz+UeH+Qx\navR5mpcoRJIkSZIkSZLq+DzwemAx0aH3hbTzZy8k0sKsAj5Z2O40YGnu/3OIgPXrKM/v3dQwYp+r\niJ74K4h87P9HpLd5CdGQ8KncukcAXyB6Ts8FDsw9dysx2eaC3GPriN76ED2mN5r8/37ABrn1LmJq\nHviLcn8vIhot+tF0Es+7034tc6tWBM4ErgDuPPn/jXPP3UH0jH/R5P/3SATABAAAIABJREFUIT4L\n/zf5/6OIz9l3gBty243iGJV+ngywS5IkSZIkSerHtcB3gf+c/P9DiNQmVwKHEoHUPxB5y8vMJwL0\nLyOCpDcSk6K+YnhV7llVPPXTRO/21+YeOxr4EPH6s174q4B7EgH6Oo7I/f1VpucEm6tzf68ievqn\nrCF662cB9rsSjQnZ6IYPEj3XFxDH+/nAs4nA/XOIhogTS8rMjPQYmSJGkiRJkiRJUr/y+awXAcdO\n/v28yX8/TLnDiYD6a4lA+4uALYB3ALcNvJbDdyKwPPf/ucD9C+ssAA7osfx9ad67fNQW0DlBaDfF\nVDQX0znB6+OJyU7vRkwEezHwq4ryRnqMDLBLkiRJkiRJs8cBlE/A2a8/A2fn/v80YoLQQ4jezN8t\n2ebxwI+JlB83EL2/s57JC0rWnwluJhoMio8V7dlj+dvSnih2Oin27N+pwbZ/p917HSLf+Qdy/9+M\nGBXxFKLB4jN09pgvGukxMsAuSZIkSZIkzQ4Lge8xdbLHQVhLZ1B0KTFh5WIiZccthfXvRARKIXow\nH0eklJnpNiFec94GRBx2Ue6xZ9E9CPx2Ili/Ye6xTYGndtluS+Am2nnMR6H43j2ywbbLSx77OXBp\n7v9vBY4hct+fVLJ+vsf6SI+RAXZJkiRJkiRpdngBEVj83pDK/yawbPLvucADKJ/cFOC+tAPRa4B/\nFp5vDaOCI7CEzsk2IQLIq+ns4b8N8OKKch4OvIpIlXI2cRwzryMC+WXmEqMFNiCC1KPyNyKvemYv\nYIfEuouBHSf/Xkfkri9aRWdaoT2A7YAfUd4Q8w/GdIwMsEuSJEmSJEkzx9rC/6tSZeQ9CXjv5PY/\nyD1+EHAVkaLjU/QXL7wD+Fzhsb9SPrlpPm1KWU7yg+jsCb6G5vLb9Pq6ioH+quO9EPg+neltrqE9\nYqDY0PA24A0l5TxtspyVwMuB84njmNmSCGjvUthuc+DXwIHAt+g87nMTf89hao/7XqwA3pz7/0Lg\nTYl1H03UFeA84rWWOYnOPPzrgI8l1h3EMepmEJ8nSZIkSZIkSWP0PiLomy3/IJ1qZDMimPnb3PrL\naPfsnQucWyjvEX3Wb2ciMJyV91+J9R5b2O8K4IlEzvZvFZ5rAR8Cnk578tTDc8+tBu5aso8f59a5\nmt4mvty3pJ67FdbZihgdcH1h3bV0pkqZSwSBi6/tJuDrwJcm65k9ng9YH1GyXQv4HfBx4Je5x5YR\n731mgghiZ8+vBB5E9KK/ADiTqZ+FU0uOxfzJ9bN1vlXy/N8Kr/8JhXW2nXy92fu2b8l+8j6fK+8C\nqt/Dfo7RqD5PkiRJkiRJkkZsY+B+RA/zsgBii+gRviy3rEmsd0qu3PlMDbD3m5N6AvgpU4P5RVvR\nDrSWLX+iM1CfLT8C7kX0fM4/fjJwF6L3+KbAC+k8BquBlxEpXLrZmAj8vpipQfMscLyc6J1+e6L+\ntxEB36JtibzqqdedLZ8p2fbtNba7lUjPUvTcxPpriEaYd5c8/jrax2tbYgLa/Doric9Lvgf8RsBf\nSsq5M3D0ZP2yhooHlNSz6N65sl5dY/2mx2iC4X+eJEmSJEmSJI3RfegeNKy7PD9X7gTRazp77nZi\n8tF+Zb3TT+yy3sFEWpl8/ZYBz5x8/hOF5/4AHEX6ta0lgrbfqFgnnwc9pZfjvZZItXMKkeKlqnfz\nRkSanrJyLiHyr6c8iXaQurj/k+icSDVvPvCrwja3ET23y3rVZ8tVRO7z4vuUX35U2NcEcDzlDSQt\n4hjVDUxnjUDLqf/ZbHKMUr3ea3+eJmpWSpIkSZIkSdL6Z4JIF7I1kQLj5urVa5lLBMm/SATtu637\nYOAiYB5TJzs9cLJuF1EvOD6TbE3knp9LBLDPn1y6mQD2JwLOa4DrgD/SPR//BHB/IvC9BPhFjW36\nMYcYCbAjEay+jQjm39CwnH2B7Wk2OW+vx0iSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmS\nJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmS\nJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmS\nJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmS\nJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmS\nJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmSJEmS\nJEmSJM0AWwB3BibGXRFJkiRJkiRJkmaCTYHvA63J5e/AHmOtkSRJkiRJkiRJM8CnaAfXs+UfwJxx\nVkoaBodnSJIkSZIk1TMH2HhymQ/cBtwKrBhnpaQh2gm4K7AVsAC4FvgzcFWX7a4Dtix5fGfg4gHW\nTxq7eeOugCRJkiRJ0phsS6StuCuwGxFEXAJsDmxCBNI3JAKLi4C5wGpgDRFc34SIrcwBVgErgeXA\n7cAtwE3AMuB64F/A5cA/iZ680nS1GfBi4CnE96KoBfxwcp0LE2WsTDy+qu/aSZIkSZIkSRqpbYBD\ngOOB7wLnEj3PbwNuJoKBxXQWg17W5fa3GrgC+BXwYeA/gLsN68VLDbyAaBSq85m+GliaKOfNJeuf\nNsR6S2NjihhJkiRJkrS+ORQ4DDgc2IXoZT4XWJhbZwVwBxH4m0v0VF9D9EBfQQTDb5/8N/s7C8rf\nQgQhtyN6sW9Eu7f74tyyIbDB5H6vICZ+XEf0iN+Ydlxm7eQ+s/X+BJwCfIdItSEN22bAScBjGm73\nLeCoksfnA28CnkF8B34IvBA/z1oPGWCXJEmSJEnrgyOJYN4hRMB648l/byHSUiwkgukXET3YzyPS\nW1wwuVw3+fywzAd2JwL+uwJ3IXqtZ6lpbp1cLwvMryJ6ul8CfI0Ifl42xPpp9toC+BmwTw/briK+\na1WpXyYY7ndLGisD7JIkSZIkaSaaDzweeC6wP5EH/Q6iJ3gLOBm4Evg3EUC/ELhhLDXtbh4RdN9l\nctkNeAgxweRq2j3frwG+CnyayOmuwbgrMeLhSiKF0NrxVmekNgTOBPbqo4xtiMlPJUmSJEmSJE1z\nRwKnEz1mVxATiN4B/IhIQXGPsdVs8DYlXu9HiJ731xM93ZcDlwJvICZlVe8OpzMH/6lEyqDZ4uP0\nN7fAWqKBSJIkSZIkSdI09mSiB/eNRID5bCLH8wPGWakR24VIg/MdIhf8TcSx+ASw+RjrNZP9nqlB\n48eNtUaD9wKiEaq4ZKM9+g2wl5V995G8MkmSJEmSJEmVjiJSu9wOnAM8kujZrciZ/VkijcwK4Ivj\nrc6MdDFTg8YvGGeFhuAl9B9Ib7rsOZJXJkmSJEmSJCnpr8DVRI/te425LtPZHOBFxEStq4BHj7c6\nM8on6QwMryRysq9P7gQcVLJcTn9B9KuAhybK3nAkr0ySJEmSJEnSFC8F1gC/ICYzVX3HEEHiM8dd\nkRliE+BDwN+Jz9tDxludkdmV/oLrq4lAuiRJkiRJkqRpZCHRE3vvcVdkhvshcNK4K6Fpaz/6C67/\nx+irLEmSJEmSJKmbueOuwHpkq3FXQNNWrwH2mzAFkSRJkiRJkiRpFssC7KuoH1z/DbB0DHWVprV5\n466AJEmSJEkSsBtwT2BbIk3MVUQe8cvGWan1iMc3bTYfmx8Sr33XinX+DLyVmGy4NYpKSZIkSZIk\nrQ/mAh8Enjvuimi9tRnwBuDflPeYXQd8H9hlXBWc4Ty+abP92GQ92D9OdMB9LDHZ67eBk4GPAi8k\nGh8kSZIkSZLUg52JAMwl466I1ksvAJZRLzXF1ZiaoimPb5rHpjPALkmSJEmSpD5sAOxU8vhuRADm\n8tFWR+u5zWinmmiynDyOys5AHt80j02bAXZJkiRJkqQB+RYRaNm38LgBdg3aFkQ+56YBzhawElg0\n+irPKB7fNI9NJwPs0oDMGXcFJEmSJEljt3XhX2kYNgR+DuzT4/YLgC0HV531jsc3bRDHZovBVUfS\n+mTeuCsgSZIkSZLWG3OAeyWeew2wVx9lrwO2ZWoQ+Drgij7KnUkWAHdPPDes43sVcE0f5Y7KxsCu\niecGcWy2A7YqPH4RcHMf5Y7KVsCdC4/tPvnvFsDeQ9jnucCKIZQrSZIkSdL/a+++wyWpq4SPf+/k\nGYaZgQGGzACDwCAIGEiuAVEQA4oRs8KurLILpnfNYVF0V0VRd5c1gRERdTEHFFEJgoIoOQ8jDOAQ\nZgjD5Pv+cartvn2r+3ao6qru/n6ep5/qW11dfbpuh+pTvzpHKp0LiVIBR9TNt0SM2rUJnZXg6OZy\nWk+eWTlUGg/38vKenjyz7h1B77fNi3ryzLp3Er3fNo/tyTOTSsASMZIkSZIkSZIkSZIkSZLUgVZH\nsO8P7N3DuNSfpqRcfkV3o2GXAJs1WPewDR5M2waXk9/2HenJs+reCOnxL8Vtk7ZtDiCe3+dTbsvi\nIg0NX/CSJEmSpIlsTtTT3R3YAOwILCs0IpXZ+pR5T+pyfa8CHuhiHYMkbft2c+BrULbvKOO3zUxg\nhy7WOcjbZkMy3Zhym6Q2DNtRXkmSJEnSxDYD/hk4K/l7JpFcB5hMJNyLsg0xsr5fRo6qO+uBY4iz\nLJS9Qd++k7u476BvG0mSJEmSJGWkUiLmFOBsYDXla143G/hhTQxXA3sWEIc6cw/tl+ZYATy/iGD7\n0MO4fdPMprOyMMOwbZ5APNfTiw5EkiRJkiSpnx0I3EZ7yaciEuzvTYnjWroboareuZb2XmMXAQuL\nCLRP3UWU+nD7jlVJsK/HbVPPBLskSZIkSVIXnglcQ2cjO+d18biLgBcSJWhOAl5GazWSf9kgnsVd\nxKLeuZKo+XwzzV9flxOvD0sAtecO4G+4fetVEuxX4LapZ4JdyohNTiVJkiRpOL2V1pPTlVGdZyeX\nFW0+1jzgRKJZ4KIG6/9xssytDdaxtsH8NW3GouKMAnsQB3eeDGxLjLpeDtwEnE+cTaHOrMXt28iD\nRKNdt40kSZIkSZIycR4Tj1a/P5ne0cXjnAA80MJjjQJ307g0w/Epy/+6i7jUW1cSZTqUjzvo7n06\nqCoj2C8oOI4ycgS7lJFJRQcgSZIkSSqVFcCXgcOI+uydmgecC3yW1kvKLAA+2eC2LwIfJUacPkyM\npH9pF/FJkiRJkiRJktSRXzB+RPg7gek1yyyisxHs84max+3Wdx8lSr7MmGD9w1IjeZA4gj1fjmBP\n5wj2xhzBLmXEEeySJEmSNJx+CFwM/D/gqmTelXRf03wW8Ctgvw7vPw3YYoJlRjtctyRJUqZscipJ\nkiRJw+mzyQXgqA7uf3yD+a8AHtdRRGGUiGdD3fzrgN90sV71xhTguJT584kzDxq9brpxFdGEdxhs\nCrwyZf4myTSP7XsZcUZK2e0APKduXuWMnG3JZ9v8gsaNmctkb+CQunk7JdPF5LNtvk308ZAkSZIk\nSRp4FxKJ7SPq5jcqETNCZ+Vfurl8IaPnqnxtQu9fG6f15JmVw870fvu+pyfPrHtH0Ptt86KePLPu\nnUTvt81je/LMpBJwBLskSZJUjMXE6LHNgTnAVsCWyWUOUTd2FpGsmgncm9y2qubyMLAyuW058Dfg\nQWLE2FLgWmBjr56Qhsoo8IeU+VsTo0i7sRS4J2X+ki7Xq97YSPprYy/is+yPOTzm0hzWWVZrSN++\nlbNG/pzDY96VwzrzsJLx22YS8HjgIeD6HB7zgRzWmYd7GL9tNiH2RZaTz+frozmsU5IkSZI0hHYn\nRrh9kqhLvRRYS/woX04kyjeQzWixjcn67k3Wv4YYefxr4FPAS4A983266lPtjmBv5AK6ew3fRpTA\n0OCxyWm+bHKazianjdnkVMqII9glSZKk7GwLPB84kjg1ensimT4DmFyz3FqixMY6YoTX6uTvKcBU\nIgm1mkiQV26/DVhIjACdQdSVnZncZ11yn8po9XVU9/W3Sy5PA/4lWdd04E7gGuDHwI8YrhGgat80\n4I3Ai4kzJ15GvI7rdVN7fT3wamKkqSRJUl8wwS5JkiR1Z2fg9cDLgW2IROQ0Ijm+gurI3IeJU7Cv\nB24Abkku65LbVgGPJJfRNh5/hDjNexOqJWWmArsAuxIj6PckkvNzkvWvAhYQJWqeCXyMKC9zDvBl\n4Ka2toAG1SRihCNEeaLaUY6LiBJE9dp57dZaDxxDjKSXJEnqG71OsG8BzCV+SEiSJEn9ag8iqf4K\nonb6ZKL26whwKXAjMTr8ZmLk+S3kV4u0krx/uG7+n1KWnUEk3iuXxxJJ+IOAzYC3A28F7gPOBr4E\nXJ1L1CqzJxKv7ZcRB43STGow/yHitdSOlcBrgB+0eT9JkqShcihRY/IRoomCJEmS1G9OJEqprCIS\nifcTo70/AzyPGD3ej2YQZW1OBa4jnteDxPNcBryjuNDUI5Ua7PfTWq30xzZYz2Ut3r9yuYg4u0KD\nzxrs+bIGezprsDdmDXapz7yWOPW1shN1DVEvstcmAW8m6mJKkiRJrXoHUbv8fmK07TnA64AdCowp\nT9sStbC/RTRLvY+ot/2+IoNS5mYRr+OfMvb3WiuXRQ3WWUnU3zLB/S8HXkic9aHhYII9XybY05lg\nb8wEu9RHXg5sYPwO1SkFxLJz8ti3F/DYkiRJ6j/HEIn11cAPidIZw2hf4qDCGiLR/sZiw1FGzqC9\npPoo0Ufg7U3WWUmwTwcOAP4ReBfwb8DxwHNoXHZGg80Ee75MsKczwd6YCXapTzyR2AlP2zFbQ9Su\nzMNMomFTvUXJY/ulI0mSpIn8iUgmf4T2a0oPqtnAe4myj2kNLtVfzqP1xPpKoiHuRCPOKwn2Xvf7\nUvmZYM+XCfZ0JtgbM8EuZaRRY5oszCUaI01rcPs04KM5PfY3iJEV++e0fkmSJA2urYgk0F3EPut7\niDIpikaqHyZqzV9HnKm6Y6ERKS8bgJ9Rrb//ENWEvCRJkhJ5Jtg/SJRkaeYo4nTTrG1VN5UkSfmZ\nRpQBOJGo13x5seFIXduFaOB4ZNGBlNyLiBr0jyk6EGXqBuCdxIGTZwPnFhuOJElSueV12t5uRDPR\niYwA7wZemlMckiQpe9sBBwEHJtPHE7V2K+4rIigpQ78vOoA+siy5qD+tTKZ3EGU25wMnESPXJUmS\n1IK8EuzvBqZOsMwKYB7ROX5b3DGXJKmMpgP7UU2mH0SMWG1mon0AqawWANsT+6hTiP3Vm4D7iwyq\n5I4lBtbsSTSCvQn4H2ApsS03Jw7K7U9s1/2TZb8BbA18k/SGmccCbwAWA48Cv07mrU5u3xP4L+Lz\nCeB8oib8CcQZCPUlferjvDZ53Es6fN7tKPPr6l+AzxB1038LHNLm/c9MmbdbMv0S2ZeT+Q3RmFXl\nNh3435T5OxBn0Z+Zw2OeR3yuDIMtgE+kzK/0Cjkzh8f8LtHou+z2Bt5WN6+S99qDfLbN54A/5rDe\nrD0LeEXdvPnJ9Onks23eA9yZw3qlobAtjRubjhKNoj5B7GDelcz7YMYxVBrrHFE33yankiQ1tz3w\nEuCTwMVEIqrVBniVy4aeRy11bh7wASLhmfZ63kgkFXYpKsCSOohIfI8CdwM/Jmp0N/tsuCm5X/38\nGTXrPbJmvbcm660sVzlDdr+aeT8mkimVv+sT67VxLkvW8d2a5fcjH/34umr3N9QI7X8/dHv5QkbP\nVfnahN6/Nk7ryTMrh53p/fZ9T0+eWfeOoPfb5kU9eWbdO4neb5vH9uSZSSWQxwj2Y2jc2HQZ8aP9\n4uTvXwGvBF5L9kn2VuwPrAOuKuCxJUkq2nTiu7B2dPr2Gax3JIN1SL1wAnAykQxtZAR4LvBE4r2y\nJP+wSu/NxIg9iHI6e9BavfodiJHo9Sqj0t9DNFCFGNn+yuT6A8T/6FBi1PoJNfd9TjL9CTEqvfas\n2No4v0yMYoexfaL2B/7UQuztGJbX1Sjw2ZT5Lwa2If5XGzN+zF6ccaDurSP9tXEMMWL2cym3deu3\nOayzrB4kffu+PpmekcNj/iGHdebhdsZvm6nA8cRI6u/l8Ji35LDOPFzJ+G2zFfAy4GrSv5+7ZdlI\nqQuVkQ/1l+uJ00BrnVhz+0E5xNBo9MWqJJ5RYD0x6l6SpEG3A3Gg+1QiSdHsjLNuLlknVKSszSMa\nN7b72v5uEcGWzNFUt8fddPYZsRmRkD85WR9E8rty+/kNHq+ScP9GzbzaEejLiBHt9ff7MWN9rua2\nLBvZ9vvrKquzgCvryascqfrXlcTv71YcnSxvs+nW3YFn66eZTXwmXVBwHGX0BGLbnF50IJLGmkF8\nYdbvNN5GehL70JplPp1hHPU7h5sB/0wcdfW0FbXqKcQR1ycXHYgkdWAGcfD6rcA5xA+uXpwKOool\nYlRu84Er6Oy1vYax5UyGUbefD+sY2xQZxpc7qGzj2lIwtaVfvtFg/rFUk/Bp66t1KFGPPSuD8Loy\nwa68tZNgrxysWkm1TrSaM8GezgR7YybYpZKqvDlrL2uJUx/T7Fqz3PUZxlHZqTsFOJuJ68eaYFea\n44nXx3VFByJJExgBdgReCnyKKNmQ1+j0tMtdxCm370iuezqoymoWkeDp5vWeRRmlfvUJsvnM2KZu\nvbWJ6ZOTebWjzB9gbFmX2kE6o4wfAV4b55c6f7otG5TXVaME+3ziN93lba7HBLvqtZNgfybV98cp\nuUU0WEywpzPB3pgJdqmkXsn4ncX3N1l+s7plt8sghgOJEfPt7NCaYFeaSoL99qIDkaQ6M4CDicZ+\n3yFqSvYqmb4OuIxoJvZyYCFja64vAe7N/ilLmTid7l7/G4harsNqGd1/hmxgbOK1Mnq9thHpaM28\nk0lX26h0lGqpmfo4dx5/18wNyuuqUYId4mzkuW2uxwS76rWTYIeoqz5KlKMqw3uk7EywpzPB3pgJ\ndqmkTmDszuKdwMwmy0+vW/5lXTz2gcA1tL9Du4LmDYg0vCoJ9keKDkTSUBsBdiK+Iz8NXEqMJOxV\nQn0Zkch6O1Eyq9n3OphgV3ntQ/fvh6t6HnV5zCCbz5T6bfieutsvIkagH9pCTLfW3O/RBnFu1u4T\nbdPeZL9NivIbIp5ndrkeE+xqpN0E+/Opvk+enUtEg8UEezoT7I2ZYJcykvVOz6Z1f/8H1Z3dNPU/\n0vfq4rFfDSxucdnKzvvZyWVFF4+rwTeLKL2wtOhAJA2FmcD+RP30yqW+nEJe1gF/Ihqg/j6ZLiW+\nN6V+d1wG6+hFuZGyympASv023L/m+oeB9zW57zeI0jGXJH8fTJSlgkis78nYmux31f2dh2MzWEdZ\nXlfvBvYlfidJZfBT4qD9FsDzkr8lSSqdrBPstaeIrwW+PsHyc+r+7qbRUCvP5QFiFMsy4B+6eCwN\nn6cBXy06CKkHPkuctfHOogMZEpXR6QdSTabvS+9Og15GJKoqCfUraH5gXOpn3TYtX0J5EqH9agnj\nt+HqmuuNejK9h+jzcHSyfCXBfjfwTeAVyd8HAz+uuV+jM24OJRqofjL5ez/iN8KfaD8hf3Cby9db\nQnleVxdhcl3lsg74NvAm4LCCY5EkqWfeSfUUrh+1sPxTGHt65G+7eOz/Jf2UyweIndZnAI9J5nna\nlFpRKREzSnSxl4bBeiyLlKeZRJLvHUSy6C56V+plLZFE/xRRbmZHxh4Yz8oSLBGjcuqmtNI6uk/Q\n97tN6O4zqNE2rG1muqzutj2p1lM/gOq+fa3aEjOVwTq1j3tk3fJHJ/PPT/4+smbZTg4wdtNQelBf\nV5aIUSPtloiBaOBeec/MzzyiwWKJmHSWiGnMEjFSSb2N6pffu1pY/k2M3cn8cxePndZc6J1EnfeK\nRZhgV+tqE+xrgAXFhiP1xAbi9a7ujRANQI8BPgP8gUim9CqhfgdwDvHdfDBRPqEXlmCCXeW0kc6T\noC8uIN6yWUjnn0cbaLwNt65b9gEi6X5+zbzKCPPK35UR35UzU0eJeuwVn6tb55uJRHplnbWjtL9R\nt2y7TVE3tLgNhul1ZYJdjXSSYN+R6vvm6ZlHNFhMsKczwd6YCXappN5M9cvv8BaW/wpjdzSv6eKx\njyF2lt8B/CVZ3xF1y5hgVztqE+yjwAcLjUbqjQ3JRd27nd4l09cQJRNOJUZ67dCD59fIEkywq5w6\nOcC1gmiyp+4S7K8Yv7oxjib9frWlUw5tsv4rGH8QsT5xXrmcXLdc7Qj2Tuq1dzKCfdBfVybY1Ugn\nCXaAB4nXVBY9DwaZCfZ0JtgbM8EuZSTrnZ7asgL3TLDsJMZ3Al/ZxWOflVwAjupiPVIjxwMfxdG9\nGnyTsLFvFvI86+UOxtdO97NJam4d8fk2qcXlLwZeSRw0UtV6Wv8N0eo2/B5x1s+hRKL8LqIeeq3b\ngBcly25NNH+eQSSrr0tZ5yuJM3gqTVTT1gnwE2AxMXL9/JTbJ7KG2B6+rqT83AdsCmxVdCCSJKWZ\nAjw3w/U9pub6/sD2TZbdG9iybt7UjOLZPJkewNgfANsk0xkZPY4G2951fy8gRocOS/f6qcDrgN/R\nuOmYBk+lJvdJdJZoKIt2EkB5yerx1wM3E+/DG5Jp7Qjx+cAzM3qsLMwEpjGY37NbAdsCc4n/70qi\nLMX9RQallo0Ay4lSMds0We4W4Gzi4NVjk8sgWEu8NztVSWxdB2xBvttwu+RSby3jP1vmA7t2sc5a\nnTRRnEQk/9YznK+rNJXfYs/Bs+I01hzis7jdfYTK62jfDu7bL7r9jIbqmTyDuo06Vdku83Hb1Nst\nme6E20bqygjwxwzXtynVJPs1wOomy+5C1E2sdQ/ZnNK0O3Ea0E3E6WQV04md2XVEGZluTSV+ZG+S\nXJ9EfPmvJ577w9gssJ9tSYzirbUOuJr4cT7oZhHNwpbjSOZh8vhkhDQxAAAgAElEQVRkuoJIBvST\nSUQpMIgR3bMLjAWq27Jda4nvjkeI75FVxKmb/WJv4n/RTV+VMplMJBbnM7avS62VwF/xLIKy24/4\nH11H7L9tSjWZsY7Yd1vJ4P0fdyb2U/9APO9OTSPe3w8Qo8mHaRs2sy/x3K/FbVJR+S12Bf31/aX8\nLSaSnVe0eb+9kvstI85GGSRbEwcerqf1M2Ea2SeZZpHrGCSTiH2Ah4AbC46lbPzNL4jc8PbEPsvy\ngmPpN1Npv39PS3ajWlvwSU2WW0h6HcxXZRRHpe5fXjXYtwbOIBLpo8BVRHmaM4i6crXP6Q7grXR/\nNFq9V1+DvVHtzkG1L9ZjG0aVZm392Nh3LtX36aIJlu2FVurwrib6h3ySaHY30ejKfrCEwanBfgKR\nTGzlf3k3sX+j8nqYOEg+bG4kXqMv73I9C5P1fKfbgAbMCjzTr5412NVIJzXYJ1MdbDCINdgrfelO\ny2Bd1mBPZw32xqzBLogE8SjRQ0ztqeSZR7s9QlpvKdWRvTs1We5k0ne4Lsw4nkamAW8EzgP+j/aS\n37sClxKlMyYD/0KM5jkGeD2RlHxTzfLbEYmTi4jTytX/3k45kndSnqYB/1x0EANoKVEi4C3AgcRB\ngUOIOsHfAe4sLjTVmAecC3w2ud6KBcT3vQbD0UQi6MiiA5GkIfdkovwcODJbkroxk/Rc7eS6qTqQ\ndYJ9DdWGPbs3WGZ/orFPvSvIt9nPJOLoHETpj9OJOosvoL1k6VmMLRvyy5Rl/ofxdbqfQCRPst7m\nyl99wmsG8T+WBt3xNC6JodasYuzo9J2IUaSfJg7WDlPJgH4xn+g/0EnD9OfS/D2zJfEaGGmyjMrh\nNcDjiP2++QXHIknDrDJq/T7aLy0jSar6BpF33X+C5dSBPJK9lZqraY17JgOfJ/2H5bdyiAXgicCn\niFOlzmqwTKvb4eBkfbW+RvoPr2+nzDsIeEaLj6Xy+CDwxbp5h5F+oEgaJAuIM3PUmTVEneK3A98l\n6oaq3GYBvyLqdHZiGtXmfrXmAj8E/kbs1F5F1LtUef1XMp1DnGEiSeq9xcSZ4hD7UjbNlaTObVU3\nVYbySLBfmkwPTLntRNKbvj0EfCGHWL4JXAacBGyTwfr2SZn3BKLMTL1GtRifnkEc6r03AufUzTuV\n8Y16pUHzQYpvFir1yqnEqOVObSS9MdAniNHtFXsRiQJPwyyv84DfJdffQDQwkiT1zhTgS8l0lCjb\nJklSKeWRYP99Mt2JaAZasQ9wSoP7/A/RIKgbM4i66D8FDkjmtZr8XN3icvc3mL9lyrwHGyybRaJf\nvbeRaMJbWxJoK+BjxYQj9cwC4N+KDkLqgX2Jg6nduJb05m0vSJm3JzZFLbtPJNMFxJlrkqTe+TTV\nQXtnMZxNqiVJfSKvBHslYf3UZDqT+FJMq0t6N40T7+14N3AGcAStd6y/HXgHcHOLy/8CuCdl/ldT\n5m1MmQftd01XeawFXkS1DBLAP1I9oCMNKhv7ahhk0dT3Sw3mN6q1vy6Dx1R+fgrcm1x/XpGBSNKQ\n+RDw5uT6o8A7C4xFkqQJ5ZFgXwNcklx/VjL9AlE/Lc1JwMoMHndBG8s+SMS2M9XRSa1YQYxCuzH5\ne21y//9sYx13t7GsyudB4Eiipj9EP4F2XkNS2W1gfNLPxr4aBod2ef8lNE6wfzll3gXA0i4fU/la\nR7WnjiPYJSl/k4DTgPfXzPs48NdiwpGkobQ/sHfRQfSbPBLsUC2j8SzgLTRuBvlD4OycYqi1AfgZ\nMVodoub7eUQtt3b9HtidKA8yO1lnWrOVmQ3u/8cOHlPlsgw4mmoS8snAC4sLR8rUg8Rr3Ma+Giab\n091ZGuuBVxP7F2lOBj5K1Gd/mNj3eWkXj6fe+U0y3Y30pvaSpGxsQvQ2+9eaeb8HPlJMOJI0dDYn\n+kleDvyJ9HLYaiCvBPtPk+n2NB7duxw4LqfHr7iBOJ1sR+DZwLkZrns5zU/t3iVl3p1Eol/97w/A\nB2r+/nBRgUg5sbGvhsmcLu67HjgGuLDJMuuIUnZbJY/1ctKboap8fl9zPa3ZvSSpezsBFwHPr5m3\nHHgJcda4JCl7mxFlMs9K/p5JDCgGmEx3v5GGTl4J9j8Bd03wGMcBf8vwMSujxu4A7kuunwT8BzEa\ns5c2Bd5aN28J8GIa12FV//k41WY7i4HDC4xFypqNfaWJrSR6c3ynjft0cvacirOU6j5m2uAJSVJ3\njgauAB5XM28t8DKqZTklSdl5CnFG7V3AfwNPKDacwdBqM9B2bUXz0d2fAn6Q8WN+LFnnhcBvgUMy\nXn+a1xAvzFpzgYOA7WrmXUe8YFf1ICb1znqiBNJ5yd8nAj8vLhwpc5XGvr+l+qPnH4l60pcWFZSU\no/W0vm90MVE2aUlu0ags7iMGT2xVdCCSNEDmAZ8hSqzVGgVeD/y65xFJ0uA6kGqe8l1FBjKoppB9\naYspxKjH7RrcfgewOofHrXgWcYoZwGuJ+tgVldIGczJ6/JfRWs3W6cSp4eov+yfTFwALmyy3JLn9\n2cBnyaZpbxlUGgc/EUvgDJNZjP9u+A3RFHoO0dj3HOCrvQ9tQtNrrr+J4g9qTiEScsP2/pkHTKO/\nnvfcZHon8TpvVgrpbuJg/g3kX+pO2ZpGZ+/JGcn0OUSN4H5TqR3/XOCxXayn8j7Zi/56f+dtBrAF\nbpNald9i/06cESdVbE2c4f4t4Eji4GW984mzg4flPbVfMt2f7p9zpZzDsGy7Vk1Lpjvjtqm3TTL1\nN//g2hs4mNhXaccaomxsO2W6NqPar3Iy0XvqDqLP26D6++/GKcQP4ayMEEnGRsn1R4hyA3nX8Zmc\nTDdh7POrPO4ksnneP2f8iOVpwK7AU2vi2AU4ghjx6anh/WNWzbTZ6+UvVBPwjydOcRwElR3e6WT7\nOaFyGyH9M/LnxGj2ScAOxI+AW3sb2oSm1VzftO7vokxm+N4/k4jXUT8978rn3XriR/9CYl9mdjJ/\nFfAAcDvVg6j99PxU1cl7svJZkvV+c69UyjXOoLv4K++TqV2uZ9CMMJyf9c1UfgPNwwS7xppHvGde\n1uD2PxMN9obp/ZTld0zl836Ytl8rpibTfv0ez5O/+Qffc6h+L7fiLuAm4GYiFzar+eJMJ/oU7U51\nMEa9JcDvGMxEe2757f8mEshpl1X0rq7PhcljHlE3f1Eyvxe13D7J+G3wE8qR8FFrjif+b62MULwx\nWfaXEy3YR/YlntPpRQeinrqXxiUv3kX18+yaXgXUhrlU42vl7KK8rabap2GYLCFeR/1kIfG6aaeW\nuvrPw7T/npxM7MOOAsdmHlFvVPZRXt7lehbi+yTNCiIhqKrKb7G8ypGqf1U+T9MuZxPJ92HzFeL5\nn5bBuu7AuvVpZhPb+IKC4yijJ+Bv/kHX6DO39nI/neVKTyAGIbXyGHfTvDJEv6rkmUezbHL6FqL7\nbCPHA3/M8PHK7icp855NNF7ttQXAM4ijSu7o5qPyY/MAhnPHUMPBxr6Shs2TgZnJ9b8UGYgkDbBL\niP5mnu0tSb2xguitdhhRn70d84BziRLJrZ75sIAYiDywskqwPxf4xATLNGt62isPEHHck8G6NqN5\nsvr+BvOPz+CxWzUV+BxRU/aXxCl3V1Cti6jsXJRMZ9P4tBip31Ua+1acWFQgktQjlVHr9zE4JeAk\nqUzuA15K1PuVJGUr7cDlu4ieGMcCv6K9cm7ziV4ZR3UQy3Op9jYaOFkk2PcAvtFkXZWC+M/L4LG6\ndR9xSsKhXazjOOCvRAL9AeBk0kcsN2oEsDO9q231GeDNjK23tDeRdK83GfgB8NYexDWIbqy5ntas\nRxoUvyS+hCHKcC0sLhRJytVi4Jjk+neBDQXGIkmDaBR4FZY1kaS8/DdwMfD/gKuSeVfS2UHNWUQu\nYL+JFmxgGu03W+0b3SbY5wHfp3FR9+9T7UT8rAwer1Ub6qa1llFtUNauVwBfALZP/p4NvJdIsjeK\nIU3eTV4hTr/4pwa3HU71dOeKtxEHQRw50JmHaq5PbbiUNBg+lkxHiBFHkjRopgBfSqajxCmwkqRs\nnQH8rOggJGmAnQAcQpR77bbJ6KnA47q4/0ayqShSSt3U454MnAU8psHtvydG/ewB/DtxGsETgMu6\neMxWfY4YUZz1Y727wfy3Ax8FHqmZV5/A7rXdaXxAYyrwD8Avkr+fBZySXP9xznENqtk111cXFoXU\nG78kOovvRnx+/Gex4agAi4gzorYmOsffRYyM+GuRQUkZ+jTVepRnMZwNiyUpTyuJMgXKTuX3/8CO\nEO3QJsl0ctOlJDXzOOCNXa7jWspRPjwX3STYP0KUB0hzMzEa+lHi1IPlwJbEyOleJNjPSS5Z263B\n/OnAVsBtNfOafal1OoK+HY1qwFe8l6gb/hRiW00mXuxL8g1rYNWeleBZABoG3yF+FFUa+9qUavDN\nI+ruv4pIsNcbJQ7S2kxb/e5DRIk9iH3ZdxYYiyQNqg8Bfys6iAGzFfG7fnnRgZTUY4sOQOpjWfST\n/FIG6yitTku2PI2o35PmfuDZwL3J36PEaEeI7rT9rNGpDF9lbHIdYJsGy95EbxLs1wDXNbn9H4ga\n8j+hekT3R3kHNcC2S6ajwMNFBiL1SG1j322LDEQ9cQLxPfdB0pPrEAdankuMau9VSTgpS5OA04D3\n18z7OJ6ZIUlZuxf4n6KDkCS17PAu778EE+zjTCFKsKQ19qw0Kbm5bn6lId6BRFH8fpVWH+404HUp\n85/SYB1fyCya5kaJEj3Njl5PJWrFr0r+tjxM5/ZKpnfiCHYNh9rGvlsWFoXyNg84l6g/3WqD7slU\nD9xK/WIT4P+Af62Z93vijE1JUrbOwLKaklQ204gyMOcR+8W1/QV37mK964FXM7Z34cDpJMH+JqrJ\nxHqnAD9NmV9JsE8jRk73q48Qo75rfZrxpREmE3WJ6/0R+FQOcTXyZ6K775eonlGwhhjZ/jXgDcAO\nxIjrFUT9XHWmcrrZDYVGIfVO7ZfjjMKiUJ7mA+cDR3Vw32nJReoHOxFn5Ty/Zt5y4CXA2kIikqTB\n9r2iAxhQlmxsbn3RAUglNInolwkxcO50ovrIC4h8YbfWE4N/L8xgXaXWboJ9C+L08DS/AT7Q4LYl\nwK3J9ae3+ZhlcjtR/mZZzbx3ML7e7PsZ/0L8HfBMev+hfidwHPFGmUIkwhYDryFGDuxL1Gr7eQGx\nDZKnJdPLiwxC6qHaxr6WRRo8s4iD4/t1sY5WR7xLRToauIJo3FSxFngZcEchEUnS4Ptj0QEMKGuv\nN9eshK40bJ5IDAC+AzirwTK1lUs6OYC3EngR0b9t4LXbiOzDwGYp8+8DXkGUG2nk18Au9HeCHeBS\nYB9itP7riRH9LyVGPj2Q3LZ/zfK3AB8Dvgxs7Gmk46X9f16VTC0P07m9qNZgv6DAOKReqm3sO9Cn\neg2pUxmbcGzXRiZuti0VaR7wGeJ01VqjxP7dr3sekSQNh1Ec2JWXZvkYwbqiA5BK4puk53abqeQz\nJ7e4/MXAK4kB10NhhGoD0onMBA4ivfb61TRuAFqxNZGIHCWS1BuIL9Z+/nKdRowMn0OMDJ9EPK91\nVMuu9KKhaacmEyV7JhGnawzjadAziZG404nX9lrif7aaSJrvQRzpXtZoBcSp5YuI1/ZvGJwdm02B\nJxFnQVxfcCzqnacQr+GLJlhuC6oJ2Asox+t+CvDU5PrPGFszrghPBx4l6jj3k8p7vxsPE9/1/WIG\ncAjwN+CqgmNRfp5GfL/fBOxJfPfXuwlY2sOYeuEg4qyUC+jus9r3SbqnEvuPlxQdSIk8njiIdT6W\nrNBYTyX213410YJDZDGwDa3lVCayL5boa+ZB/F1bbw4xktnf/INrCpG3XABsTnpOt5GLqPbLOJT4\nbTtC5NEaeQi4jeE5o2YmcDDEhj6zxTu9lvR/xGVE87NGZhBv2K2Sv0eIZqcVDxFNUa8kfow/0mI8\nZbEd8UK7hWj6t4I4aDCF+KLcgzi48APKl2w/hPixeTPw+WJD6alZRAfkQ4gPmXqjxOvxauL/dzHN\nR6b/RzK9msHqirwTkWS7gdY/J9T/DiC+RM+cYLnnEQn2+ynP634W1QT7z6n2nijKU4nvhDMLjqNd\nb8hgHd8nvTF4WW1BfCfcTv/9v9S6pxOJh30b3P5z4Ou9C6dn9iI+H6+ku1J2vk/SHUTs459ZcBxl\ncjNRLrPRKecaXrcTnyXnFB1IibyRyBssxfeMem860afvN5hgH1QfJ3KS7biXaHT6k5p5TycOAn6I\n6EG4OzEKfpQ4eHU3cA3Dk1ivWECSYG/VJGIjjdZdHqLxP2oK8E6ifEz9/RpdHiLK0DQ7GlI2H2D8\n81hd9/cdVA8wlMnPiPjeW3QgPXQCUcqnldfjymR6XJP1HVSz/OvyCrog+xLP6/SiA1FP3Utrp3F9\nnXh9tHoWVC/Mpfp+XFRwLBDfBVcXHUQHrqP17+20y23EKPh+spCIfSjqAw6xZq/bs2lvRE8/uZF4\nji/vcj0L8X2SZgUmJSR17ivEZ+tpRQciaSC18ztuJdE7Mm2feD2t9894JnAu1cFvg6xSzWK01San\n+xJHmut9nDhKUW9b4gjYR4lTEFo1G3gP8Bdg7zbuV6T5KfNqTzl+CDiSOJ22TBYQnYFhOOqvzyPe\n4J+l9cZ7cyZe5O/vi0eA73UQl9SvnpZMbew7eHbq4r7riZrW1uVXP7mEaP5uKQtJkiQNiw3EwNt3\nJH8/RIxc73af+M3AUUQlj7Sc6UBqNcH+tJR5jwCfTpm/FVFvr60h8nUWEWU5/qGLdfRKs8YA64EX\nEwcMyuYYogb7MuBPBceSt/nEa/KoDu/frI7zD4lSGU8mTouRhoGNfQdbp6Xa1hPfLRdmGIuUt/uI\nZvVrig5EkiRJ6oEbiIojOwLPJgajZum/kukc4G0Zr7u0Wk2wH5gy71uMTyiOEKeN7t5NUInZRL2f\nPTJYV552aHLbPwO/6FUgbXpVMv1J06X63yyiic5+XaxjojrOPyLqmkrD4rnJdD0mUwfReR3cZyXw\nIiwdof4ySuwP3VF0IJIkSVIOKjXR7yAGlgCcRPQSXJbTY54H/C65/gaaD1odGK0m2NMS5memzDue\n5qPOVxEJGYgRchOddjCbKLsxe4LlijIJeHyD204BvkiM8vwJkegtiz2oxj3o5WFOJRoxdmoj2R/N\nk/rd65Lp+VgKZBB9gPb+rxcTpeR+kE84Um7OoL+a8UqSJEntOJCohb4Tve0Z84lkWlueeqBNaXG5\n7ev+vpv4QV2/rnel3PdB4HNE86iriYZ4TyeSlscDTyTqXr6U9CT0nsQ/5vgWY+2lPUhP/n+TauPQ\n9xGnXOxIeRogVUavr6VcDQqztojoyt6Na4F1GcQilckios/F1kTPiLuIz/S/tnDfg6ieWXRWLtH1\nl262ZVndBBwOfA3YtclyVxCNyc/F2tXqPytJ329VYzOS6TZUz2RS/AYq00AaSZKkiluTS6/9lKgG\nsQVRVvmnBcTQU60m2Det+/sHxMjeWoczvlzK+UQ91toGn5cSCfb9gYeBXyeXDwKnA0ekPP6xREPV\nW1qMt1fSOuL+Fng9kWzYGziupxG15hXJ9DfE/2BQPT+DdXwpg3VIZTAPOJE4wLYo5fZR4oyWyROs\nx8a+rW/LtO7r/eIS4uy1pxAHwhcQz+s+4DbgIvr7IIL0IcrXgL7sNk+mBxM9aFQ1FKc+S5IktWgd\n8G3gTQzJCPZWrSN+WFcur05Z5tS6ZS4GpqUs98Lk9g3AJnW3jRCNU0dTLmd0+yRy8DPGxngd1aan\nM4nRfZXbylJL/hCqMZ1YcCx5O5P011Krl9sYf3BpmOxLbIfTiw5EXTsBeIDWXvcbmLge8YuIpGvZ\nzKX6PNIS31loZ1tuJBrIqPwWEv8za8gPtsp7cznV0djD4Ebieb+8y/UcTHf7VYN8sUmupE59hfgc\nOa3oQCQNvAuJz5v6gc2LkvnN8gDrgT+2+XgvpbqvNL/N+/aLyrYbbbUG+yN1f1+SssxeNdfXEzV6\n16Ysd1kynUQk8GqNEsX2/zflfi9k4pGVvTSHGIlf8TfgSCLxMpMY2dlNY828vKrm+qDXX1/QxX3X\nEweSrC+tfjaPKN/x2eR6KyZRPVDYyHeBP3QRVz/qZFuOEKVjJJXLGcDqooOQJEmSBtjva67vU1gU\nPdJqgv3emuuVkb31tqi5/nNitEyaO6l2qt2/wTInAX+pmzeX8Qn5Ih1LdYT+KqKm0G3Ac4A/k17q\npmhTgZck128Ebi4wll7o9MfzeqK00YUZxiL12nyiTNdRHdx3JulnIA2rbrblplg6QCqbYS1v1a0V\nRQdQYvbrkSRJ/eoBYl/mnozXu5TqoNVdMl536bSaYK9NqD9ElBCoV7tjWd8AtV5lFHujBPtq4B0p\n88tyxGMy1fIqG4FXEs9pJ6I+/W4FxTWRI6meljHoo9cBLu/gPiuJ8heWCVA/mwX8is7PohkhztKR\n21IaNKO0f3qrwiD37enWRKXVJEmSyuo+omTmoTmtG2CrHNZdKq0m2K+uuf5gg2VqdywnKqtxZTJt\nljD/BfCnunlbpC1YgGOJZDrAW4iyARAvyFa3aRGGqTwMRA32dkq8XEycJfGDXKIpp/nAYuBJRG3V\nvYmzRdTfTgUe18X9N+JIxQq3pTRY1hBnqkmSJEnDZEPdtNYyYsBp1u5PpvU9OAfOCK2NRpkCTE+u\njxIlUepNpVpSYB3p9dcrJlNtLlVf373WNMaeWj/RenthhCifMML4eGqfV71HiURLkWYRcTf6Hw6i\nScRrt9mBj43E/zHtQ2YQjRDv6Sk03i4biNf3DCIRYfOu/jGJ+IzqxkbiM6vfjBCfcwC30l0fBhju\nbTlsKq8dP+8G2yYM1z5QxUzi8+xaqgNEOjGCJa8aGcUyMZI6M534XfZXYPOCY5E02CYnl3XEvks7\nNqGz37aV/dC1DOa+0t9zBiNEx9OJbEY0Nq00Gd2P8Yn5hcB5yfW/EGU2GtkOuCC5/mwa1wJ/KvDF\nmr8/D3y8hXjzdApRx/w84ATGJs0PAL7e4H6HEwmfIi0AtgFuYbiad04mRmbvQbyWR4kzMe4izs5Y\nXlxoPfdqosdBKyUrVhDNHL8FvC/PoJSpk4GXd7mOjxBngPSbTYErkuuHEj9UujHM23LYVPZLfk58\nt2swHUaMzBm2Js3nEfvpJwI/KTYUSVKd/wReCHwF+HDBsUhSI9cD1xGfV62aTFQwmQG8Gzgnh7iK\nthPwy3bv9CsiMTlK47o8tcv8wwTruz9ZrlnyYv+a9Y0S/5AiHUAk1C8lfVTj0xgbb+1lj96EKKWa\nR5QyavT6bHY5vYB41bnr6Oz/XLncRiSq+9Fcqs+jlYPHExnmbTlsFhL/M/tvaBDdyMT73JKkYnyF\n+Iw+rehAJKmJ9bTfx+ipVH8bPzHziMphEclzbKde+Bdqrj+/wTLvozqi+0s0r+VcqcO+d5Nl6svB\n3N5k2bzNAM4AlgDPw1P+1T/mA+cDR3V4/8lNbts0Wf9Ih+tW9ro5/X89cZbDMJ3h0ozbUpIkSZKk\n9h2bTO+jeqb5wGonwf5dYGly/dWkF6i/GPj35PpuRKPSRp1ir0umezZ5zPr6uddMHGZuPkXE82zg\nbwXGIbVjFnFmyX5drCOtr8BM4IdEqZ17gato/l5W7zTra9HMeuAY4MIMY+l3bktJkiRJktqzmPhN\nDJFPHvieh+0k2NcBH0iubw68tcFyHwL+O7n+JOIoxZEpy7WSYH9SzfX7iNruRXgd8Hqi1tANBcUg\ndeJU4HFd3H8U+L+U+S8Anlvz917Eh2az0e7qjfMmXmSclUTfDMtjjOW2HGsO0WdkBdEsMe27XZIk\nSZI0vKYQVU2mEDmlzxYbTjlNIkapjxIlUpolx99OtTPtBmDrutufkdy2ltjoaa6kWq/nPzqOujtz\nied6LzEasdnlKhrX4r28btnP9/JJaChtS3f1o0eJ13SajzZYfnE+T0Vt2I04s6DV//FFRP3pQZB1\nDfZh3pZpPsvY57saeEyhEWVnIdZg1+CyBrsklZc12CX1g3ZqsH+O6m/Gb+QWUTn8vQZ7J3feA1iV\n3Pl6mtdZ34foppo2snW7miDSGoA+p+b2h4BtOgk2A5MY27y108utxPaqXH6IdauVr6Pp/nV7UoN1\nn9xg+V3zeSpq00HAzTT/315OnJUzSJ9DWSfYYXi3ZZq0pq8nFBpRdhZigl2DywS7JJWXCXZJ/aDV\nBPuHqP5WXAXskGdQJfD3BHujkePNXA8cRxyF2B34GXA4Mcqv3l+Awxqs506ivu0mxCjB62tum0Mc\n8ah4P3BXB7FmYSPwTGAX0mtR1zoEOL3Bbc8Hrs4wLmkiu3R5/yXEaT1pLkmZdwFwS5ePqWxcQows\n3pv4nN6M+NB/ELib6GexvLDo+ovbsupvjD8gXtR3syRJkiSpHCYRvSv/tWbex4G/FhNOf3kf1aMS\nNxCj1dt1dXL/E2vmTSZGvFfW/X36Z1TgsTQe4fjMAuPScPownY9cXwc8ucm6JwOnEAm3h4BvAVvm\n8SSkNuQxgl1VhxNl3Srb+HwGp+/CQhzBrsHlCHZJKi9HsEvqB81GsG9C5G5rc0qXANN6E1qhuioR\nU6t26P+jwL8AU9u4/4+S+34m+Xsu8L2adf4WmNVtkD30bRonLD9aYFwaTu+n8+T6i9t4nH45AKbB\nZ4I9fzsQTY6fQnuN0stuISbYNbhMsEtSeZlgl9QPGiXYd2Js/8xRYiDm9r0LrVCZJdgBXkck1ysr\nXEKUkNmkhftWCt//CjieOHWgsp7/a3EdZbEP1aauaZflwOaFRadhdAztJ9dXEOWMNBzOAd5ZdBAZ\nyjvBPp2ot97OgWT1h4WYYNfgMsEuSeVlgl1SP0hLsB8N3MfYnNIa4Om9Da1QmSbYARYDlzJ+o55H\nJG9eRZRIOQR4BjH67U2kNw99iGis2E+jYhcTBxYmSl5eCAFU0IUAAAtZSURBVCwoJkQNoS2IOtGt\nJtcvIpJMGh6bE0eXlxL1xftdngn2/yR2Ks7OeL0qh4WYYNfgMsEuSeVlgl1SP6hNsM8Dvsr4nNJG\n4BWFRFecMU1OO6mdnuafiCT6G4A9iVo7h9G4yWm9e4EfAGcRCZ+9M4orT68BDgQOAFppGHsIcCtR\ni+gXRINYKU9vBj5C887N1wGfB35NNBjO6jNB/eEwotzXZcRn76eB3xUaUedm11x/DN2XGJsHvJI4\nMj+NODi8FN8jg2jbZDoX/78aPNOT6fb4+pakstksmc7Hz2hJ5TUCzCRyTO8HtkpZ5lNEr81h+izb\nsXJlhEioZG0KkYyYRjRAq6/TWjmysZHqqfbLc4gjbzOIbVh7tGZjzd8kt48Q22BSzd8biGZxUi9M\nJ95rlffiRqqvwQ1FBaVSmUwcYKk0rXyEKHu1vrCIOjMjmS4Btu7g/iPEe2VmMh0BVhHbQ4NrEvHD\ndjVxJp00SKYTn2VXAnsUHIskaaypxP73X4gBIpJURlsSec5G1UYeBR7uXTilMUJ1MEtPTCVKEWzO\n2Nq1e1JNRs/tZUCSpFQHAH8gaqk9RJxd9FWi1Nc2BcaVpwOB9wK/J3YMHiQOLJxcZFDqub1xX0SS\nJEmS6jUrN3w2/VXmeyBtTfUfslPBsUiSqg4AzgRWEqN67yeS7tcDpwLPpsdHajO0O9FY+/tEMv0e\nYpT6amL00AnFhSZJkiRJUqk0Sq5fTP/mBTJV9BGGOUTyBmLk2NUFxiJJSncI8C/AEUQJlsnEZ/cM\n4G7gJiIxfTNwG3BLMi3SXGCX5LIrURZhLyL2hUQJs02Ikeq3AF8mDijc2/tQJUmSJEkqrdGUefcB\n+wJ39DiWUio6wT6dGDEI8CSiLIEkqbyeQDSzfgGRYJ9NlP5aD6wgPtOnEQ1ClxHJ6+uAPwFriFrm\nq+qmtZd1KY85K3mcWURSvH46GdgNWEyMTt+R6AVSqQE3B9g0ub6CqK9+BZFQ/xYxil2SJEmSJI1X\nn2AfBY4EflZALKXUbYL9WcCbgIOJ0YJLgK8DH6eaOG9mKtVGn4cQpxZIkvrDY4GnEDXM9yNKfU0l\nkttT6pZdRSTP1xGNdSunlE1Klp1KtanoGuBOIlE+LbnPWiKJX7nvCJFYr1xmU23QWrEmWf+9wA3A\nJcClxE7Amq6fvSRJkiRJg68+wf5l4NgiAimrThPsU4AvAq9tcPtFRCmBiTrIblKzzAHAZR3GI0kq\nhwXESPL9iTOTFhOJ8oeJz/wR4jtkGuOT8K0aJRLulWT9KmA+sJwYMf9nIpH+F+DaZBlJkiRJktS+\n2gT7SuAxwN8KiqWUOk1ufI7GyXWI0ej/DbxmgvXMrLn+aIexSJLK457k8uu6+QuALYhSLXOIEedb\nAFsR5WTm1FwqB1+nAw8ll5VEKZf7kvWvrLntQaLmu4l0SZIkSZLy8yFMrmdiH2AjjTvIVi4biZq4\nzexcs/yuOcUrSZIkSZIkSWpfJXe7nOjFpjqTOrjP82mttMwI8IwJltmh5rpHPyRJkiRJkiSpfM6g\ntZ6bQ6eTBPu2bSy71QS3V0atP0Cc5i9JkiRJkiRJKpfvFR1AWXWSYF/RxrL3THD7ocn0ug7ikCRJ\nkiRJkiTlaxT4Y9FBlFUnCfZlLS63HvhZk9unAYcn13/cQRySJEmSJEmSpHytJnK9ysg+TNzgdBQ4\nZYL1HFez7OK8gpUkSZIkSZIkdWQUeLDoIAbRbTROrG8EPk3z0fGza9Zxbq6RSpIkSZIkSZI6cT1w\ndtFBDKJ/pJpQfxT4H+CrwIeBfVu4//8m910PPC6nGCVJkiRJkiRJnZtCZ2XGNYHJwOVUk+zn0vqG\n/rea+70rl+gkSZIkSZIkSSqxHYF7qCbLfw1s22T52cB/1Sz/fWAk5xglSZIkSZIkSSqlfYDbqSbN\nHwHOBF4EPIEo//Ic4FPA3TXLfReY1vtwJUmSJEmSJEkqjwXA92jc9LT28ghRFmZyIZFKkiRJkiRJ\nkpSRLEu0HAgcBxwJbFN32/XAOcAXgaUZPqYkSZIkSZKk7EwCDgMeD8wHNgKXAv+XXJfUAzOBrYg3\n4ZSCY5EkSZIkSZLU3GTgw8Aa0itTPAwcVVh0kiRJkiRJkiSV0G7AXYxPqt8AXFvz9zrgoIJilCRJ\nkiRJkiSpVI5k/Kj1R4EDktsPr7vt7QXEKEmSJEmSJElSqRxNejmYVyS3n5Ry27/2PkxJkiRJkiRJ\nkspjJ2AV4xPotwBTgS0b3G6CfXi8mDjD4THAtIJjKS0bkEqSJEmSJEnDZRLwNWBmym1nEbXW1yaX\n2mU2ApflHp3K4lPA9sn1DcBS4gDMzTXTm4FbiYMxQ2mk6AAkSZIkSZIk9dRzgB+lzN8AHAZckPz9\nNeBVNbd/G3hZrpGpTF5LjF7fFViUTOelLDcKLCM9+X4LsLIXwRbFBLskSZIkSZI0PCYDlwOPS7lt\nDbAncFvNvBcQTU9HgV/kHp3KbguqCfdFjE2+b8n4fPMocC+Nk+/LexJ1jkywS5IkSZIkScPjYOCi\nBrddC+xNlIKR2jWH8Un3ynRbojRRvZU0Tr4vIxL0pWaCXZIkSZIkSRpcewHPBdYTI9RfDTypwbKr\ngLcCs5PrZwCrexCjBt9MItGelnzfkfReoauI+u5pyfelREmjwplglyRJkiRJkgbTZOAaYPcO7/8W\n4NPZhSOlmgrszPjk+yJgITA95T5rgSWkJ99vS27vibQjA5IkSZIkSZL63wbge8DbiNHAI8DcJss/\nSJSHGSFGvF+Sd4ASsA64MbnUm0SMcE9Lvu9CNGGttwH4K+nJ91uI90JmHMEuSZIkSZIkDYd3Aac0\nuO0GYDHWX1f/GAG2IT35viswL+U+o8BdjE++30aUQ7oG3wOSJEmSJEmS6kwCfkskGNMuHysuNCkX\nWwAHAK8EPgB8HbgCeIBIoqe9D45q90EsESNJkiRJkiQNvk2BfRrctgH4bg9jkfIyiygdkzaifUei\nL0G9dcDDxPvgjnYf0AS7JEmSJEmSNPj2oXH99buAq3oYi9SNuTQuC7MNcbZGvZXAlVTLwtSWh7mL\nGL3eERPskiRJkiRJ0uA7rMltvyDqT0tlsSXjk+iV6RaM7y06CtwLXEp6Ev3evAI1wS5JkiRJkiQN\ntknA0xvcthE4q4exSBAJ8m1pnERPO9tiIzHa/LeMT6LfQoxS77n6TL8kSZIkSZKkwTIXuJ30pOUK\nYCfgwZ5GpGEwGdiBsSVcKtNdiXrp9dYDf2V88vxm4FZgVe5Rt8kR7JIkSZIkSdJga1Z//QJMrqtz\n04CFpCfRd05ur7cGWEJ6En0JsDbfkLNlgl2SJEmSJEkabM3qr1seRhOZBexCehJ9R2Kker1HgBtI\nT6L/FdiQe9Q9YoJdkiRJkiRJGlzN6q+vAH7Ww1jUX34O7AVsQ7yO6q0AriQ9iX4X0Xh04JlglyRJ\nkiRJkgbXpkSJmDTfw/IwamxHYCpwKelJ9HuLC02SJEmSJEmS8ncwMZK4/rKOxol3CWBG0QH0g7Sh\n/ZIkSZIkSZIGwzMazL8M+EsvA1HfWV10AJIkSZIkSZLUCzsBO9fNmwT8lvGj1zfQvPGpJEmSJEmS\nJEkDbwuiHnYlef5Lom42wBzgfsYn2C/tfZiSJEmSJEmSJJXLuYxPoL80ue2glNusvS5lyBrskiRJ\nkiRJUn/aEnhayvwdk+mLU277KNZelyRJkiRJkiQNuW2BVYwfob4/MANYXnfbT4oJU5IkSZIkSZKk\ncqlPsN9LNDuFGKlem1y/gUi6S5IkSZIkSZI09OqbmK4AjgMuYWxy/bZkWUmSJEmSJEmSlHgGsJ7x\nzUwrl+8DUwuLTpIkSZIkSZKkEpsHfAy4GrgVuBk4G9i3yKCkYfD/ARMXr8XuK8mkAAAAAElFTkSu\nQmCC\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 172,
       "width": 748
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "vlnPart = aScore.getElementById('Violin I.')\n",
    "mRange = vlnPart.measures(4, 7)\n",
    "mRange.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we want to gather all :class:`~music21.pitch.Pitch` objects from this\n",
    "measure range, we can use the :meth:`pitches <music21.stream.Stream.pitches>` property.\n",
    "This returns a list of all Pitch objects. All pitch objects have\n",
    ":meth:`pitchClass <music21.pitch.Pitch.pitchClass>` and\n",
    ":meth:`pitchClassString <music21.pitch.Pitch.pitchClassString>` properties, providing either integer\n",
    "or string representations, respectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'A4, F#4, G4, G4, B4, E5, G5, G5, G5, C#6, E6, E6, E6, G6, C#5'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "', '.join([str(p) for p in mRange.pitches])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[9, 6, 7, 7, 11, 4, 7, 7, 7, 1, 4, 4, 4, 7, 1]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[p.pitchClass for p in mRange.pitches]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we want to label the notes in our measure range with the Note's pitch class\n",
    "representation, we can iterate over the notes and assign the pitch class\n",
    "representation to the Note's lyric.  This is a common way to annotate Note and\n",
    "Chord objects in music21. The results can be displayed with the `show()` method.\n",
    "\n",
    "Here is the image from when we were using a Beethoven Quartet as an example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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dSAR5Hpp7/EAi73CVz9Izmv+eUWH9fO/oA2h/56oqGymwDzEqbdiGGWDvNhLi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wJfAk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\n9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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 175,
       "width": 748
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for n in mRange.flat.notes:\n",
    "    if n.tie is None or n.tie.type == 'start':\n",
    "        n.lyric = n.pitch.pitchClassString\n",
    "mRange.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Chords as Forte Set Classes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Any music21 Chord can be interpreted as a Forte set class. Additional, a wide\n",
    "variety of analytical features, derived from the Forte set class, are available\n",
    "as methods of the chord. \n",
    "\n",
    "For an example, lets create a sequence of generated aggregate-completing\n",
    "trichords stored on a Stream. That is, we will construct chords with pitch\n",
    "classes, drawing them from a list of all pitch classes. These pitches will be\n",
    "supplied to a Chord object and stored on a Stream."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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3A/cA/0AM5vbt5D07QGm63bOSdhSdlL8hM30hjbNoiswAzie+xM5usG69kjYX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\ndwNfB57uc1skSZIkSdIE8P8BOkxqaxoa07IAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 56,
       "width": 748
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "aStream = stream.Stream()\n",
    "src = list(range(12)) # cheate a list of integers 0 through 11\n",
    "src = src[2:4] + src[0:2] + src[8:9] + src[4:8] + src[9:12] # recombine\n",
    "for i in range(0, 12, 3):\n",
    "    aStream.append(chord.Chord(src[i:i + 3]))\n",
    "    \n",
    "aStream.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These Chords, like all Chords in music21, can be interpreted as Forte set\n",
    "classes. The Chord object offers numerous methods that retrieve data from the\n",
    "set class representation of the Chord. The following is just a sampling of some\n",
    "of the many relevant methods. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<023>\n",
      "<148>\n",
      "<567>\n",
      "<9AB>\n"
     ]
    }
   ],
   "source": [
    "for c in aStream: \n",
    "    print(c.orderedPitchClassesString)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3-2B\n",
      "3-11A\n",
      "3-1\n",
      "3-1\n"
     ]
    }
   ],
   "source": [
    "for c in aStream: \n",
    "    print(c.forteClass)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3-2\n",
      "3-11\n",
      "3-1\n",
      "3-1\n"
     ]
    }
   ],
   "source": [
    "for c in aStream: \n",
    "    print(c.forteClassTnI)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 2, 3]\n",
      "[1, 4, 8]\n",
      "[5, 6, 7]\n",
      "[9, 10, 11]\n"
     ]
    }
   ],
   "source": [
    "for c in aStream: \n",
    "    print(c.normalOrder)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<013>\n",
      "<037>\n",
      "<012>\n",
      "<012>\n"
     ]
    }
   ],
   "source": [
    "for c in aStream: \n",
    "    print(c.primeFormString)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 1, 1, 0, 0, 0]\n",
      "[0, 0, 1, 1, 1, 0]\n",
      "[2, 1, 0, 0, 0, 0]\n",
      "[2, 1, 0, 0, 0, 0]\n"
     ]
    }
   ],
   "source": [
    "for c in aStream: \n",
    "    print(c.intervalVector)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To annotate the Chords stored on the Stream with their Forte name, we can\n",
    "iterate over the Stream and assign the Forte name to each Chord's `lyric`\n",
    "attribute."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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jUJ71VuA24H8Tk7l9L/nMTlCaHvekpB1FF+WvzKyfS+tRNEXmA2cTX2Ifa1G2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\nJEmSJEmSJEmSJEmSJEnSMPn/AazG+PkhENvsAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 69,
       "width": 748
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for c in aStream:\n",
    "    c.lyric = c.forteClass\n",
    "aStream.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can use the `itertools.combinations` function to find all possible subsets of a chord for a given cardinality. (Hat tip to John Chittum for the hint).  Here is the `all tri-chord hexachord` which contains within it all possible three-note chords under inversion and transposition:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'all tri-chord hexachord'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import itertools\n",
    "c = chord.Chord([0, 1, 2, 4, 7, 8])\n",
    "c.commonName"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we'll test this create a set to hold the Forte number for each trichord and see that all twelve of them are there:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cc = set()\n",
    "for i in itertools.combinations(c.pitches, 3):\n",
    "    cc.add(chord.Chord(i).forteClassNumber)\n",
    "cc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Creating and Processing Twelve-Tone Matrices"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The music21 :ref:`moduleSerial` module provides a Stream-based representation\n",
    "of a 12-Tone row, as well as the ability to view these rows as a matrix.\n",
    "Additionally, numerous 12-tone rows from works are available as classes. \n",
    "\n",
    "For example, we can create an instance of the row from Alban Berg's *Violin\n",
    "Concerto*, use the `show()` method to display its contents as text, and then\n",
    "create and print a :class:`~music21.serial.TwelveToneMatrix` object. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{0.0} <music21.note.Note G>\n",
      "{1.0} <music21.note.Note B->\n",
      "{2.0} <music21.note.Note D>\n",
      "{3.0} <music21.note.Note F#>\n",
      "{4.0} <music21.note.Note A>\n",
      "{5.0} <music21.note.Note C>\n",
      "{6.0} <music21.note.Note E>\n",
      "{7.0} <music21.note.Note G#>\n",
      "{8.0} <music21.note.Note B>\n",
      "{9.0} <music21.note.Note C#>\n",
      "{10.0} <music21.note.Note E->\n",
      "{11.0} <music21.note.Note F>\n"
     ]
    }
   ],
   "source": [
    "aRow = serial.getHistoricalRowByName('RowBergViolinConcerto')\n",
    "aRow.show('text')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  0  3  7  B  2  5  9  1  4  6  8  A\n",
      "  9  0  4  8  B  2  6  A  1  3  5  7\n",
      "  5  8  0  4  7  A  2  6  9  B  1  3\n",
      "  1  4  8  0  3  6  A  2  5  7  9  B\n",
      "  A  1  5  9  0  3  7  B  2  4  6  8\n",
      "  7  A  2  6  9  0  4  8  B  1  3  5\n",
      "  3  6  A  2  5  8  0  4  7  9  B  1\n",
      "  B  2  6  A  1  4  8  0  3  5  7  9\n",
      "  8  B  3  7  A  1  5  9  0  2  4  6\n",
      "  6  9  1  5  8  B  3  7  A  0  2  4\n",
      "  4  7  B  3  6  9  1  5  8  A  0  2\n",
      "  2  5  9  1  4  7  B  3  6  8  A  0\n"
     ]
    }
   ],
   "source": [
    "aMatrix = aRow.matrix()\n",
    "print(aMatrix)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We might divide this row into trichords, present each of those trichords as\n",
    "Chords, and label the resulting pitch classes and Forte set class. As shown\n",
    "above, we can set the `lyric` attribute to assign a single line of text. If we\n",
    "need to assign multiple lines of text, the Note and Chord method\n",
    ":meth:`~music21.note.GeneralNote.addLyric` can be used to add successive lines."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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SkvU/Bw4s23EzIqjdzmHMDq4DvJ/G5KWpXYCziKBsJ7YE3gr8UfaqGxTuxdYl36XB9TXA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\nw/8Hw+4GTc1gctgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 88,
       "width": 748
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bStream = stream.Stream()\n",
    "for i in range(0, 12, 3):\n",
    "    c = chord.Chord(aRow[i:i + 3])\n",
    "    c.addLyric(c.primeFormString)\n",
    "    c.addLyric(c.forteClass)\n",
    "    bStream.append(c)\n",
    "bStream.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This should give a decent introduction to working with post-tonal music -- we'll return to this when we discuss searching for post-tonal structures, but there's still a lot to find in a Stream, and we want to take it one step at a time -- the best way to do so is to understand :ref:`Chapter 26, Stream Iteration and Filtering <usersGuide_26_iterators>`"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
